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<h2 class="title">
<a id="fuzzy-query"></a>Fuzzy Query<a class="edit_me edit_me_private" rel="nofollow" title="Editing on GitHub is available to Elastic" href="https://github.com/elastic/elasticsearch-definitive-guide/edit/2.x/270_Fuzzy_matching/30_Fuzzy_query.asciidoc">edit</a>
</h2>
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<p>The <a href="/guide/en/elasticsearch/reference/2.4/query-dsl-fuzzy-query.html" class="ulink" target="_top"><code class="literal">fuzzy</code> query</a> is the fuzzy equivalent of
the <code class="literal">term</code> query. You will seldom use it directly yourself, but understanding
how it works will help you to use fuzziness in the higher-level <code class="literal">match</code> query.</p>
<p>To understand how it works, we will first index some documents:</p>
<div class="pre_wrapper lang-json">
<pre class="programlisting prettyprint lang-json">POST /my_index/my_type/_bulk
{ "index": { "_id": 1 }}
{ "text": "Surprise me!"}
{ "index": { "_id": 2 }}
{ "text": "That was surprising."}
{ "index": { "_id": 3 }}
{ "text": "I wasn't surprised."}</pre>
</div>
<p>Now we can run a <code class="literal">fuzzy</code> query for the term <code class="literal">surprize</code>:</p>
<div class="pre_wrapper lang-json">
<pre class="programlisting prettyprint lang-json">GET /my_index/my_type/_search
{
  "query": {
    "fuzzy": {
      "text": "surprize"
    }
  }
}</pre>
</div>
<p>The <code class="literal">fuzzy</code> query is a term-level query, so it doesn’t do any analysis.  It
takes a single term and finds all terms in the term dictionary that are
within the specified <code class="literal">fuzziness</code>. The default <code class="literal">fuzziness</code> is <code class="literal">AUTO</code>.</p>
<p>In our example, <code class="literal">surprize</code> is within an edit distance of 2 from both
<code class="literal">surprise</code> and <code class="literal">surprised</code>, so documents 1 and 3 match. We could reduce the
matches to just <code class="literal">surprise</code> with the following query:</p>
<div class="pre_wrapper lang-json">
<pre class="programlisting prettyprint lang-json">GET /my_index/my_type/_search
{
  "query": {
    "fuzzy": {
      "text": {
        "value": "surprize",
        "fuzziness": 1
      }
    }
  }
}</pre>
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<h3 class="title">
<a id="_improving_performance_2"></a>Improving Performance<a class="edit_me edit_me_private" rel="nofollow" title="Editing on GitHub is available to Elastic" href="https://github.com/elastic/elasticsearch-definitive-guide/edit/2.x/270_Fuzzy_matching/30_Fuzzy_query.asciidoc">edit</a>
</h3>
</div></div></div>
<p>The <code class="literal">fuzzy</code> query works by taking the original term and building a
<em>Levenshtein automaton</em>—like a big graph representing all the strings
that are within the specified edit distance of the original string.</p>
<p>The fuzzy query then uses the automaton to step efficiently through all of the terms
in the term dictionary to see if they match.  Once it has collected all of the
matching terms that exist in the term dictionary, it can compute the list of
matching documents.</p>
<p>Of course, depending on the type of data stored in the index, a fuzzy query
with an edit distance of 2 can match a very large number of terms and
perform very badly. Two parameters can be used to limit the
performance impact:</p>
<div class="variablelist">
<dl class="variablelist">
<dt>
<span class="term">
<code class="literal">prefix_length</code>
</span>
</dt>
<dd>
The number of initial characters that will not be “fuzzified.”  Most
spelling errors occur toward the end of the word, not toward the beginning.
By using a <code class="literal">prefix_length</code> of <code class="literal">3</code>, for example, you can signficantly reduce
the number of matching terms.
</dd>
<dt>
<span class="term">
<code class="literal">max_expansions</code>
</span>
</dt>
<dd>
If a fuzzy query expands to three or four fuzzy options, the new options may be
meaningful.  If it produces 1,000 options, they are essentially
meaningless.  Use <code class="literal">max_expansions</code> to limit the total number of options that
will be produced. The fuzzy query will collect matching terms until it
runs out of terms or reaches the <code class="literal">max_expansions</code> limit.
</dd>
</dl>
</div>
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